As ever increasing quantities of digital multichannel data are generated through the use of such multispectral scanners as the four-channel scanner on the ERTS-1 satellite, the S192 thirteen-channel scanner on Skylab, and numerous aircraft scanners including the Bendix Corporation's 24-channel scanner, the need for improved processing capabilities has become critical. The current methods of processing this data use a maximum likelihood pattern recognition program such as LARSYS II. While such a program provides an optimum classification scheme, at least in the sense of minimizing the cost of misclassification, the computer processing time required to produce a classification map increases substantially as the number of channels of data increases. When digital pattern recognition techniques are applied to the processing of terrain classification data for extended areas, the cost of processing all of the data becomes prohibitive. As a consequence, in such cases it is practical to process only a small fraction of the data that is acquired. Although grey maps or color composites for a single channel can readily be made from such "screened" data, these maps cannot be made to include any information contained in the multispectral nature of the data.